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R

compute.es

Compute Effect Sizes

Several functions are available for calculating the most widely used effect sizes (ES), along with their variances, confidence intervals and p-values. The output includes ES's of d (mean difference), g (unbiased estimate of d), r (correlation coefficient), z' (Fisher's z), and OR (odds ratio and log odds ratio). In addition, NNT (number needed to treat), U3, CLES (Common Language Effect Size) and Cliff's Delta are computed. This package uses recommended formulas as described in The Handbook of Research Synthesis and Meta-Analysis (Cooper, Hedges, & Valentine, 2009).

Functions (18)

chi_to_es

Chi-Squared Statistic to Effect Size

compute.es-package

Compute Effect Sizes in R

d_to_es

Mean Difference (d) to Effect size

f.ancova_to_es

ANCOVA F-statistic to Effect Size

f_to_es

F-test to Effect Size

fail_to_es

Failure groups to Effect Size

lor_to_es

Log Odds Ratio to Effect Size

mean_anc_to_es

Mean Values from ANCOVA F-statistic to Effect Size

mean_anc_to_es2

Mean Values from ANCOVA F-statistic with Pooled SD to Effect Size

mean_to_es

Means to Effect Size

mean_to_es2

Means with Pooled SD to Effect Size

p.ancova_to_es

One or Two-tailed p-value from ANCOVA to Effect Size

p_to_es

p-value to Effect Size

prop_to_es

Proportions to Effect Size

r_to_es

Correlation coefficient (r) to Effect Size

tt.ancova_to_es

t-test Value from ANCOVA to Effect Size

tt_to_es

t-test Value to Effect Size

ztor

Internal anRpackage objects

compute.es

Compute Effect Sizes

v0.2-5
GPL-2
Authors
AC Del Re
Initial release
2020-04-01

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